- Building RESTful Python Web Services
- Building RESTful Python Web Services
- Credits
- About the Author
- Acknowledgments
- About the Reviewer
- www.PacktPub.com
- Preface
- 1. Developing RESTful APIs with Django
- Designing a RESTful API to interact with a simple SQLite database
- Understanding the tasks performed by each HTTP method
- Working with lightweight virtual environments
- Setting up the virtual environment with Django REST framework
- Creating the models
- Managing serialization and deserialization
- Writing API views
- Making HTTP requests to the API
- Test your knowledge
- Summary
- 2. Working with Class-Based Views and Hyperlinked APIs in Django
- Using model serializers to eliminate duplicate code
- Working with wrappers to write API views
- Using the default parsing and rendering options and move beyond JSON
- Browsing the API
- Designing a RESTful API to interact with a complex PostgreSQL database
- Understanding the tasks performed by each HTTP method
- Declaring relationships with the models
- Managing serialization and deserialization with relationships and hyperlinks
- Creating class-based views and using generic classes
- Taking advantage of generic class based views
- Working with endpoints for the API
- Creating and retrieving related resources
- Test your knowledge
- Summary
- 3. Improving and Adding Authentication to an API With Django
- Adding unique constraints to the models
- Updating a single field for a resource with the PATCH method
- Taking advantage of pagination
- Customizing pagination classes
- Understanding authentication, permissions and throttling
- Adding security-related data to the models
- Creating a customized permission class for object-level permissions
- Persisting the user that makes a request
- Configuring permission policies
- Setting a default value for a new required field in migrations
- Composing requests with the necessary authentication
- Browsing the API with authentication credentials
- Test your knowledge
- Summary
- 4. Throttling, Filtering, Testing, and Deploying an API with Django
- Understanding throttling classes
- Configuring throttling policies
- Testing throttling policies
- Understanding filtering, searching, and ordering classes
- Configuring filtering, searching, and ordering for views
- Testing filtering, searching, and ordering
- Filtering, searching, and ordering in the Browsable API
- Setting up unit tests
- Writing a first round of unit tests
- Running unit tests and checking testing coverage
- Improving testing coverage
- Understanding strategies for deployments and scalability
- Test your knowledge
- Summary
- 5. Developing RESTful APIs with Flask
- Designing a RESTful API to interact with a simple data source
- Understanding the tasks performed by each HTTP method
- Setting up a virtual environment with Flask and Flask-RESTful
- Declaring status codes for the responses
- Creating the model
- Using a dictionary as a repository
- Configuring output fields
- Working with resourceful routing on top of Flask pluggable views
- Configuring resource routing and endpoints
- Making HTTP requests to the Flask API
- Test your knowledge
- Summary
- 6. Working with Models, SQLAlchemy, and Hyperlinked APIs in Flask
- Designing a RESTful API to interact with a PostgreSQL database
- Understanding the tasks performed by each HTTP method
- Installing packages to simplify our common tasks
- Creating and configuring the database
- Creating models with their relationships
- Creating schemas to validate, serialize, and deserialize models
- Combining blueprints with resourceful routing
- Registering the blueprint and running migrations
- Creating and retrieving related resources
- Test your knowledge
- Summary
- 7. Improving and Adding Authentication to an API with Flask
- Improving unique constraints in the models
- Updating fields for a resource with the PATCH method
- Coding a generic pagination class
- Adding pagination features
- Understanding the steps to add authentication and permissions
- Adding a user model
- Creating a schemas to validate, serialize, and deserialize users
- Adding authentication to resources
- Creating resource classes to handle users
- Running migrations to generate the user table
- Composing requests with the necessary authentication
- Test your knowledge
- Summary
- 8. Testing and Deploying an API with Flask
- 9. Developing RESTful APIs with Tornado
- Designing a RESTful API to interact with slow sensors and actuators
- Understanding the tasks performed by each HTTP method
- Setting up a virtual environment with Tornado
- Declaring status codes for the responses
- Creating the classes that represent a drone
- Writing request handlers
- Mapping URL patterns to request handlers
- Making HTTP requests to the Tornado API
- Test your knowledge
- Summary
- 10. Working with Asynchronous Code, Testing, and Deploying an API with Tornado
- Understanding synchronous and asynchronous execution
- Refactoring code to take advantage of asynchronous decorators
- Mapping URL patterns to asynchronous request handlers
- Making HTTP requests to the Tornado non-blocking API
- Setting up unit tests
- Writing a first round of unit tests
- Running unit tests with nose2 and checking testing coverage
- Improving testing coverage
- Other Python Web frameworks for building RESTful APIs
- Test your knowledge
- Summary
- 11. Exercise Answers
- Chapter 1, Developing RESTful APIs with Django
- Chapter 2, Working with Class-Based Views and Hyperlinked APIs in Django
- Chapter 3, Improving and Adding Authentication to an API With Django
- Chapter 4, Throttling, Filtering, Testing, and Deploying an API with Django
- Chapter 5, Developing RESTful APIs with Flask
- Chapter 6, Working with Models, SQLAlchemy, and Hyperlinked APIs in Flask
- Chapter 7, Improving and Adding Authentication to an API with Flask
- Chapter 8, Testing and Deploying an API with Flask
- Chapter 9, Developing RESTful APIs with Tornado
- Chapter 10, Working with Asynchronous Code, Testing, and Deploying an API with Tornado
In order to work with the different samples for Python 3.5.x, you will need any computer with an Intel Core i3 or higher CPU and at least 4 GB RAM. You can work with any of the following operating systems:
- Windows 7 or greater (Windows 8, Windows 8.1 or Windows 10)
- macOS Mountain Lion or greater
- Any Linux version capable of running Python 3.5.x and any modern browser with JavaScript support
You will need Python 3.5 or greater installed on your computer.
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